Variation of Geomagnetic Index Empirical Distribution and Burst Statistics Across Successive Solar Cycles
The overall level of solar activity, and space weather response at Earth, varies within and between successive solar cycles and can be characterized by the statistics of bursts, i.e., time series excursions above a threshold. We consider nonoverlapping 1‐year samples of the auroral electrojet index...
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description | The overall level of solar activity, and space weather response at Earth, varies within and between successive solar cycles and can be characterized by the statistics of bursts, i.e., time series excursions above a threshold. We consider nonoverlapping 1‐year samples of the auroral electrojet index (AE) and the SuperMAG‐based ring current index (SMR), across the last four solar cycles. These indices, respectively, characterize high latitude and equatorial geomagnetic disturbances. We suggest that average burst duration τ̄ $\bar{\tau }$ and burst return period R̄ $\bar{R}$ form an activity parameter, τ̄/R̄ $\bar{\tau }/\bar{R}$ which characterizes the fraction of time the magnetosphere spends, on average, in an active state for a given burst threshold. If the burst threshold takes a fixed value, τ̄/R̄ $\bar{\tau }/\bar{R}$ for SMR tracks sunspot number, while τ̄/R̄ $\bar{\tau }/\bar{R}$ for AE peaks in the solar cycle declining phase. Level crossing theory directly relates τ̄/R̄ $\bar{\tau }/\bar{R}$ to the observed index value cumulative distribution function (cdf). For burst thresholds at fixed quantiles, we find that the probability density functions of τ and R each collapse onto single empirical curves for AE at solar cycle minimum, maximum, and declining phase and for (−)SMR at solar maximum. Moreover, underlying empirical cdf tails of observed index values collapse onto common functional forms specific to each index and cycle phase when normalized to their first two moments. Together, these results offer operational support to quantifying space weather risk which requires understanding how return periods of events of a given size vary with solar cycle strength.
Plain Language Summary
Earth's magnetosphere and ionosphere have their own space weather. Space weather storms can cause technological problems including electrical grid damage and satellite system disruption. The overall driving of space weather follows the solar cycle of activity which has a period of approximately 11‐years. Geomagnetic indices, based on magnetic field observations at the Earth's surface, provide almost continuous monitoring of magnetospheric and ionospheric activity. We analyze two geomagnetic index time series, AE and SMR, which track activity in the auroral region and around the Earth's equator, respectively. We identify bursts or excursions above thresholds in the AE and SMR time series. We find that the ratio of average burst duration to return period provides a useful a |
doi_str_mv | 10.1029/2021JA029986 |
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Plain Language Summary
Earth's magnetosphere and ionosphere have their own space weather. Space weather storms can cause technological problems including electrical grid damage and satellite system disruption. The overall driving of space weather follows the solar cycle of activity which has a period of approximately 11‐years. Geomagnetic indices, based on magnetic field observations at the Earth's surface, provide almost continuous monitoring of magnetospheric and ionospheric activity. We analyze two geomagnetic index time series, AE and SMR, which track activity in the auroral region and around the Earth's equator, respectively. We identify bursts or excursions above thresholds in the AE and SMR time series. We find that the ratio of average burst duration to return period provides a useful activity parameter which tracks the solar cycle in a well‐defined way. No two solar cycles are the same, each solar maximum has a different strength. However, the distributions of the bursts, and the observations from which they are constructed, have properties that repeat from one solar cycle to the next. These results provide constraints that could be used in model predictions for the statistics of future space weather on solar cycle scales.
Key Points
For fixed value thresholds annual mean burst duration‐return period ratio tracks solar cycle for SMR but peaks near cycle decline for AE
Parameters of bursts in AE and SMR with thresholds at fixed quantile share the same distributions for successive solar cycle maxima
Tails of AE and SMR empirical distributions follow a solar cycle invariant functional form for solar cycle maximum, minimum, and decline</description><identifier>ISSN: 2169-9380</identifier><identifier>ISSN: 2169-9402</identifier><identifier>EISSN: 2169-9402</identifier><identifier>DOI: 10.1029/2021JA029986</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Auroral electrojet ; Auroral electrojets ; Bursts ; Constraint modelling ; crossing theory ; Distribution functions ; Earth ; Earth magnetosphere ; Earth surface ; Electrojets ; Empirical analysis ; Equator ; Equatorial regions ; Geomagnetic disturbances ; geomagnetic indices ; Geomagnetism ; Ionosphere ; Level crossings ; Magnetic fields ; Parameters ; Probability density functions ; Quantiles ; Ring currents ; Solar activity ; Solar cycle ; Solar maximum ; Space weather ; Statistical methods ; Sunspot numbers ; Sunspots ; Thresholds ; Time series</subject><ispartof>Journal of geophysical research. Space physics, 2022-01, Vol.127 (1), p.n/a</ispartof><rights>2022. The Authors.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>info:eu-repo/semantics/openAccess</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3692-21f84f317ae90b115c9c3cd2a8734dedd5ca146a3cf3b7e8bc34ca3ea5ad44363</citedby><cites>FETCH-LOGICAL-c3692-21f84f317ae90b115c9c3cd2a8734dedd5ca146a3cf3b7e8bc34ca3ea5ad44363</cites><orcidid>0000-0003-0053-1584 ; 0000-0002-6959-2046 ; 0000-0001-7100-9502 ; 0000-0003-4484-6588</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2021JA029986$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2021JA029986$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,1427,4010,26544,27900,27901,27902,45550,45551,46384,46808</link.rule.ids></links><search><creatorcontrib>Bergin, A.</creatorcontrib><creatorcontrib>Chapman, S. C.</creatorcontrib><creatorcontrib>Moloney, N. R.</creatorcontrib><creatorcontrib>Watkins, N. W.</creatorcontrib><title>Variation of Geomagnetic Index Empirical Distribution and Burst Statistics Across Successive Solar Cycles</title><title>Journal of geophysical research. Space physics</title><description>The overall level of solar activity, and space weather response at Earth, varies within and between successive solar cycles and can be characterized by the statistics of bursts, i.e., time series excursions above a threshold. We consider nonoverlapping 1‐year samples of the auroral electrojet index (AE) and the SuperMAG‐based ring current index (SMR), across the last four solar cycles. These indices, respectively, characterize high latitude and equatorial geomagnetic disturbances. We suggest that average burst duration τ̄ $\bar{\tau }$ and burst return period R̄ $\bar{R}$ form an activity parameter, τ̄/R̄ $\bar{\tau }/\bar{R}$ which characterizes the fraction of time the magnetosphere spends, on average, in an active state for a given burst threshold. If the burst threshold takes a fixed value, τ̄/R̄ $\bar{\tau }/\bar{R}$ for SMR tracks sunspot number, while τ̄/R̄ $\bar{\tau }/\bar{R}$ for AE peaks in the solar cycle declining phase. Level crossing theory directly relates τ̄/R̄ $\bar{\tau }/\bar{R}$ to the observed index value cumulative distribution function (cdf). For burst thresholds at fixed quantiles, we find that the probability density functions of τ and R each collapse onto single empirical curves for AE at solar cycle minimum, maximum, and declining phase and for (−)SMR at solar maximum. Moreover, underlying empirical cdf tails of observed index values collapse onto common functional forms specific to each index and cycle phase when normalized to their first two moments. Together, these results offer operational support to quantifying space weather risk which requires understanding how return periods of events of a given size vary with solar cycle strength.
Plain Language Summary
Earth's magnetosphere and ionosphere have their own space weather. Space weather storms can cause technological problems including electrical grid damage and satellite system disruption. The overall driving of space weather follows the solar cycle of activity which has a period of approximately 11‐years. Geomagnetic indices, based on magnetic field observations at the Earth's surface, provide almost continuous monitoring of magnetospheric and ionospheric activity. We analyze two geomagnetic index time series, AE and SMR, which track activity in the auroral region and around the Earth's equator, respectively. We identify bursts or excursions above thresholds in the AE and SMR time series. We find that the ratio of average burst duration to return period provides a useful activity parameter which tracks the solar cycle in a well‐defined way. No two solar cycles are the same, each solar maximum has a different strength. However, the distributions of the bursts, and the observations from which they are constructed, have properties that repeat from one solar cycle to the next. These results provide constraints that could be used in model predictions for the statistics of future space weather on solar cycle scales.
Key Points
For fixed value thresholds annual mean burst duration‐return period ratio tracks solar cycle for SMR but peaks near cycle decline for AE
Parameters of bursts in AE and SMR with thresholds at fixed quantile share the same distributions for successive solar cycle maxima
Tails of AE and SMR empirical distributions follow a solar cycle invariant functional form for solar cycle maximum, minimum, and decline</description><subject>Auroral electrojet</subject><subject>Auroral electrojets</subject><subject>Bursts</subject><subject>Constraint modelling</subject><subject>crossing theory</subject><subject>Distribution functions</subject><subject>Earth</subject><subject>Earth magnetosphere</subject><subject>Earth surface</subject><subject>Electrojets</subject><subject>Empirical analysis</subject><subject>Equator</subject><subject>Equatorial regions</subject><subject>Geomagnetic disturbances</subject><subject>geomagnetic indices</subject><subject>Geomagnetism</subject><subject>Ionosphere</subject><subject>Level crossings</subject><subject>Magnetic fields</subject><subject>Parameters</subject><subject>Probability density functions</subject><subject>Quantiles</subject><subject>Ring currents</subject><subject>Solar activity</subject><subject>Solar cycle</subject><subject>Solar maximum</subject><subject>Space weather</subject><subject>Statistical methods</subject><subject>Sunspot numbers</subject><subject>Sunspots</subject><subject>Thresholds</subject><subject>Time series</subject><issn>2169-9380</issn><issn>2169-9402</issn><issn>2169-9402</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>3HK</sourceid><recordid>eNp9kMFLwzAUxosoOOZu3g14tZrkpW1yrHPOjYHg1GtI01QyunYmrbr_3sw58OS7vI_H7_t470XROcHXBFNxQzEl8zwowdOjaEBJKmLBMD0-aOD4NBp5v8KheBiRZBDZV-Ws6mzboLZCU9Ou1VtjOqvRrCnNF5qsN9ZZrWp0Z33nbNH_sKop0W3vfIeWXXD7YPAo1671Hi17rY339sOgZVsrh8ZbXRt_Fp1UqvZm9NuH0cv95Hn8EC8ep7Nxvog1pILGlFScVUAyZQQuCEm00KBLqngGrDRlmWhFWKpAV1BkhhcamFZgVKJKxiCFYXSxz9Vut1cjm9YpSTCGTFIODAJxuSc2rn3vje_kqu1dE5aSNKVMEAZiR10dcsJVzlRy4-xauW3IkruPy78fDzjs8U9bm-2_rJxPn_IkFZzCN78bgXE</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Bergin, A.</creator><creator>Chapman, S. C.</creator><creator>Moloney, N. R.</creator><creator>Watkins, N. W.</creator><general>Blackwell Publishing Ltd</general><general>American Geophysical Union</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>8FD</scope><scope>H8D</scope><scope>KL.</scope><scope>L7M</scope><scope>3HK</scope><orcidid>https://orcid.org/0000-0003-0053-1584</orcidid><orcidid>https://orcid.org/0000-0002-6959-2046</orcidid><orcidid>https://orcid.org/0000-0001-7100-9502</orcidid><orcidid>https://orcid.org/0000-0003-4484-6588</orcidid></search><sort><creationdate>202201</creationdate><title>Variation of Geomagnetic Index Empirical Distribution and Burst Statistics Across Successive Solar Cycles</title><author>Bergin, A. ; Chapman, S. C. ; Moloney, N. R. ; Watkins, N. W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3692-21f84f317ae90b115c9c3cd2a8734dedd5ca146a3cf3b7e8bc34ca3ea5ad44363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Auroral electrojet</topic><topic>Auroral electrojets</topic><topic>Bursts</topic><topic>Constraint modelling</topic><topic>crossing theory</topic><topic>Distribution functions</topic><topic>Earth</topic><topic>Earth magnetosphere</topic><topic>Earth surface</topic><topic>Electrojets</topic><topic>Empirical analysis</topic><topic>Equator</topic><topic>Equatorial regions</topic><topic>Geomagnetic disturbances</topic><topic>geomagnetic indices</topic><topic>Geomagnetism</topic><topic>Ionosphere</topic><topic>Level crossings</topic><topic>Magnetic fields</topic><topic>Parameters</topic><topic>Probability density functions</topic><topic>Quantiles</topic><topic>Ring currents</topic><topic>Solar activity</topic><topic>Solar cycle</topic><topic>Solar maximum</topic><topic>Space weather</topic><topic>Statistical methods</topic><topic>Sunspot numbers</topic><topic>Sunspots</topic><topic>Thresholds</topic><topic>Time series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bergin, A.</creatorcontrib><creatorcontrib>Chapman, S. C.</creatorcontrib><creatorcontrib>Moloney, N. R.</creatorcontrib><creatorcontrib>Watkins, N. W.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>NORA - Norwegian Open Research Archives</collection><jtitle>Journal of geophysical research. Space physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bergin, A.</au><au>Chapman, S. C.</au><au>Moloney, N. R.</au><au>Watkins, N. W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Variation of Geomagnetic Index Empirical Distribution and Burst Statistics Across Successive Solar Cycles</atitle><jtitle>Journal of geophysical research. Space physics</jtitle><date>2022-01</date><risdate>2022</risdate><volume>127</volume><issue>1</issue><epage>n/a</epage><issn>2169-9380</issn><issn>2169-9402</issn><eissn>2169-9402</eissn><abstract>The overall level of solar activity, and space weather response at Earth, varies within and between successive solar cycles and can be characterized by the statistics of bursts, i.e., time series excursions above a threshold. We consider nonoverlapping 1‐year samples of the auroral electrojet index (AE) and the SuperMAG‐based ring current index (SMR), across the last four solar cycles. These indices, respectively, characterize high latitude and equatorial geomagnetic disturbances. We suggest that average burst duration τ̄ $\bar{\tau }$ and burst return period R̄ $\bar{R}$ form an activity parameter, τ̄/R̄ $\bar{\tau }/\bar{R}$ which characterizes the fraction of time the magnetosphere spends, on average, in an active state for a given burst threshold. If the burst threshold takes a fixed value, τ̄/R̄ $\bar{\tau }/\bar{R}$ for SMR tracks sunspot number, while τ̄/R̄ $\bar{\tau }/\bar{R}$ for AE peaks in the solar cycle declining phase. Level crossing theory directly relates τ̄/R̄ $\bar{\tau }/\bar{R}$ to the observed index value cumulative distribution function (cdf). For burst thresholds at fixed quantiles, we find that the probability density functions of τ and R each collapse onto single empirical curves for AE at solar cycle minimum, maximum, and declining phase and for (−)SMR at solar maximum. Moreover, underlying empirical cdf tails of observed index values collapse onto common functional forms specific to each index and cycle phase when normalized to their first two moments. Together, these results offer operational support to quantifying space weather risk which requires understanding how return periods of events of a given size vary with solar cycle strength.
Plain Language Summary
Earth's magnetosphere and ionosphere have their own space weather. Space weather storms can cause technological problems including electrical grid damage and satellite system disruption. The overall driving of space weather follows the solar cycle of activity which has a period of approximately 11‐years. Geomagnetic indices, based on magnetic field observations at the Earth's surface, provide almost continuous monitoring of magnetospheric and ionospheric activity. We analyze two geomagnetic index time series, AE and SMR, which track activity in the auroral region and around the Earth's equator, respectively. We identify bursts or excursions above thresholds in the AE and SMR time series. We find that the ratio of average burst duration to return period provides a useful activity parameter which tracks the solar cycle in a well‐defined way. No two solar cycles are the same, each solar maximum has a different strength. However, the distributions of the bursts, and the observations from which they are constructed, have properties that repeat from one solar cycle to the next. These results provide constraints that could be used in model predictions for the statistics of future space weather on solar cycle scales.
Key Points
For fixed value thresholds annual mean burst duration‐return period ratio tracks solar cycle for SMR but peaks near cycle decline for AE
Parameters of bursts in AE and SMR with thresholds at fixed quantile share the same distributions for successive solar cycle maxima
Tails of AE and SMR empirical distributions follow a solar cycle invariant functional form for solar cycle maximum, minimum, and decline</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2021JA029986</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0003-0053-1584</orcidid><orcidid>https://orcid.org/0000-0002-6959-2046</orcidid><orcidid>https://orcid.org/0000-0001-7100-9502</orcidid><orcidid>https://orcid.org/0000-0003-4484-6588</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Auroral electrojet Auroral electrojets Bursts Constraint modelling crossing theory Distribution functions Earth Earth magnetosphere Earth surface Electrojets Empirical analysis Equator Equatorial regions Geomagnetic disturbances geomagnetic indices Geomagnetism Ionosphere Level crossings Magnetic fields Parameters Probability density functions Quantiles Ring currents Solar activity Solar cycle Solar maximum Space weather Statistical methods Sunspot numbers Sunspots Thresholds Time series |
title | Variation of Geomagnetic Index Empirical Distribution and Burst Statistics Across Successive Solar Cycles |
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